chromatographR: Chromatographic Data Analysis Toolset

preprocess

R Documentation

Preprocess time/wavelength data

Description

Standard pre-processing of response matrices, consisting of a time axis and a spectral axis (e.g. HPLC-DAD/UV data). For smooth data, like UV-VIS data, the size of the matrix can be reduced by interpolation. By default, the data are baseline-corrected in the time direction (baseline.corr) and smoothed in the spectral dimension using cubic smoothing splines (smooth.spline.

Usage

preprocess(
  X,
  dim1,
  dim2,
  remove.time.baseline = TRUE,
  spec.smooth = TRUE,
  maxI = NULL,
  parallel = NULL,
  interpolate_rows = TRUE,
  interpolate_cols = TRUE,
  mc.cores,
  cl = 2,
  show_progress = NULL,
  ...
)

Arguments

`X`	A numerical data matrix, or list of data matrices. Missing values are not allowed. If rownames or colnames attributes are used, they should be numerical and signify time points and wavelengths, respectively.
`dim1`	A new, usually shorter, set of time points (numerical). The range of these should not exceed the range of the original time points.
`dim2`	A new, usually shorter, set of wavelengths (numerical). The range of these should not exceed the range of the original wavelengths.
`remove.time.baseline`	Logical, indicating whether baseline correction should be done in the time direction, according to `baseline.corr`. Default is TRUE.
`spec.smooth`	Logical, indicating whether smoothing should be done in the spectral direction, according to `smooth.spline`. Default is TRUE.
`maxI`	if given, the maximum intensity in the matrix is set to this value.
`parallel`	Logical, indicating whether to use parallel processing. Defaults to TRUE (unless you're on Windows).
`interpolate_rows`	Logical. Whether to interpolate along the time axis (`dim1`). Defaults to TRUE.
`interpolate_cols`	Logical. Whether to interpolate along the spectral axis (`dim2`). Defaults to TRUE.
`mc.cores`	How many cores to use for parallel processing. Defaults to 2. This argument has been deprecated and replaces with `cl`.
`cl`	Argument to `pblapply` or `mclapply`. Either an integer specifying the number of clusters to use for parallel processing or a cluster object created by `makeCluster`. Defaults to 2. On Windows integer values will be ignored.
`show_progress`	Logical. Whether to show progress bar. Defaults to `TRUE` if `pbapply` is installed.
`...`	Further optional arguments to `baseline.corr`.

Value

The function returns the preprocessed data matrix (or list of matrices), with row names and column names indicating the time points and wavelengths, respectively.

Note

Adapted from the preprocess function in the alsace package by Ron Wehrens.

Author(s)

Ethan Bass

References

Wehrens, R., Bloemberg, T.G., and Eilers P.H.C. 2015. Fast parametric time warping of peak lists. Bioinformatics 31:3063-3065. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/bioinformatics/btv299")}.
Wehrens, R., Carvalho, E., Fraser, P.D. 2015. Metabolite profiling in LC–DAD using multivariate curve resolution: the alsace package for R. Metabolomics 11:1:143-154. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s11306-014-0683-5")}.

Examples


data(Sa)
new.ts <- seq(10,18.66,by=.01) # choose time-points
new.lambdas <- seq(200, 318, by = 2) # choose wavelengths
Sa_pr <- preprocess(Sa[[1]], dim1 = new.ts, dim2 = new.lambdas)

ethanbass/chromatographR documentation built on April 17, 2025, 10:55 a.m.